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Mitogen Inducible Gene-6 Is a Prognostic Marker for Patients with Colorectal Liver Metastases
David B Donner1, Dan T Ruan1, Kan Toriguchi1
1Department of Surgery, Division of Surgical Oncology, and The Comprehensive Cancer Center, The University of California San Francisco, San Francisco, CA. 94143; The Helen Diller Family Comprehensive Cancer Center, The University of California San Francisco, San Francisco, CA. 94143.
Purpose:
Prognostic schemes that rely on clinical variables to predict outcome after resection of colorectal metastases remain imperfect. We hypothesized that molecular markers can improve the accuracy of prognostic schemes.
Methods:
We screened the transcriptome of matched colorectal liver metastases (CRCLM) and primary tumors from 42 patients with unresected CRCLM to identify differentially expressed genes. Among the differentially expressed genes identified, we looked for associations between expression and time to disease progression or overall survival. To validate such associations, mRNA levels of the candidate genes were assayed by qRT-PCR from CRCLM in 56 additional patients who underwent hepatectomy.
Results:
Seven candidate genes were selected for validation based on their differential expression between metastases and primary tumors and a correlation between expression and surgical outcome: lumican; tissue inhibitor metalloproteinase 1; basic helix-loop-helix domain containing class B2; fibronectin; transmembrane 4 superfamily member 1; mitogen inducible gene 6 (MIG-6); and serpine 2. In the hepatectomy group, only MIG-6 expression was predictive of poor survival after hepatectomy. Quantitative PCR of MIG-6 mRNA was performed on 25 additional hepatectomy patients to determine if MIG-6 expression could substratify patients beyond the clinical risk score. Patients within defined clinical risk score categories were effectively substratified into distinct groups by relative MIG-6 expression.
Conclusions:
MIG-6 expression is inversely associated with survival after hepatectomy and may be used to improve traditional prognostic schemes that rely on clinicopathologic data such as the Clinical Risk Score.
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